AIMC Topic: Deep Learning

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A deep learning framework for reconstructing Breast Amide Proton Transfer weighted imaging sequences from sparse frequency offsets to dense frequency offsets.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Amide Proton Transfer (APT) technique is a novel functional MRI technique that enables quantification of protein metabolism, but its wide application is largely limited in clinical settings by its long acquisition time. One way to reduce the scanning...

Establishment of an intelligent analysis system for clinical image features of melanonychia based on deep learning image segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Melanonychia, a condition that can be indicative of malignant melanoma, presents a significant challenge in early diagnosis due to the invasive nature and equipment dependency of traditional diagnostic methods such as nail biopsy and dermatoscope ima...

Impact of spectrum bias on deep learning-based stroke MRI analysis.

European journal of radiology
PURPOSE: To evaluate spectrum bias in stroke MRI analysis by excluding cases with uncertain acute ischemic lesions (AIL) and examining patient, imaging, and lesion factors associated with these cases.

CausalMixNet: A mixed-attention framework for causal intervention in robust medical image diagnosis.

Medical image analysis
Confounding factors inherent in medical images can significantly impact the causal exploration capabilities of deep learning models, resulting in compromised accuracy and diminished generalization performance. In this paper, we present an innovative ...

Sepsis Important Genes Identification Through Biologically Informed Deep Learning and Transcriptomic Analysis.

Clinical and experimental pharmacology & physiology
Sepsis is a life-threatening disease caused by the dysregulation of the immune response. It is important to identify influential genes modulating the immune response in sepsis. In this study, we used P-NET, a biologically informed explainable artific...

BERTAgent: The development of a novel tool to quantify agency in textual data.

Journal of experimental psychology. General
Pertaining to goal orientation and achievement, agency is a fundamental aspect of human cognition and behavior. Accordingly, detecting and quantifying linguistic encoding of agency are critical for the analysis of human actions, interactions, and soc...

Estimating canopy leaf angle from leaf to ecosystem scale: a novel deep learning approach using unmanned aerial vehicle imagery.

The New phytologist
Leaf angle distribution (LAD) impacts plant photosynthesis, water use efficiency, and ecosystem primary productivity, which are crucial for understanding surface energy balance and climate change responses. Traditional LAD measurement methods are tim...

Rethinking boundary detection in deep learning-based medical image segmentation.

Medical image analysis
Medical image segmentation is a pivotal task within the realms of medical image analysis and computer vision. While current methods have shown promise in accurately segmenting major regions of interest, the precise segmentation of boundary areas rema...

Multi-task learning for joint prediction of breast cancer histological indicators in dynamic contrast-enhanced magnetic resonance imaging.

Computer methods and programs in biomedicine
OBJECTIVES: Achieving efficient analysis of multiple pathological indicators has great significance for breast cancer prognosis and therapeutic decision-making. In this study, we aim to explore a deep multi-task learning (MTL) framework for collabora...